Department of Artificial Intelligence and Machine Learning (AI&ML)

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The theory and development of computer systems that can perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation and interpretation are formalized as AI. Machine learning is a method of data analysis that automates analytical model building.
The adoption of artificial intelligence/ Machine Learning (AI/ML) is growing worldwide. Organizations worldwide are adopting AI/ML in their business transformation journey for agility, resilience, innovations, and scalability.
With this backdrop, CBIT offers a four-year under-graduate B.E(CSE AI/ML & AI/ML ) for laying a strong foundation by using the principles and technologies that consist of many facets of Artificial Intelligence including logic, knowledge representation, probabilistic models, and Machine Learning.
Students shall be able to acquire the ability to design intelligent solutions for various business problems in a variety of domains and business applications and also explore fields such as neural networks, natural language processing, robotics, deep learning, computer vision, reasoning, and problem-solving.
This program is best suited for students seeking to build world-class expertise in Artificial Intelligence and Machine Learning and emerging technologies which help to stand apart in the crowd and grow careers in the upcoming technological era.

Department Vision
• To produce professionals in artificial intelligence and machine learning through the best possible education, acquire international recognition as a destination, and advance society in exciting and creative ways.

Department Mission
• Impart rigorous training to generate knowledge through the state-of-the-art concepts and technologies in Artificial Intelligence and Machine Learning.
• Develop technical proficiency in students through creativity and leadership.
• Encourage lifelong learning, social responsibility, environmental conservation, and professional ethics.
• Establish centres of excellence in leading areas of computer and artificial intelligence disciplines.

Programs offered
The Department offers Under Graduate program in B.E. (AIML) with an intake of 60 students and B.E. (CSE-AIML) with an intake of 60 students.
     1. B.E. (AIML)
     2. B.E. (CSE-AIML)

B.E. Program Outcomes (PO’s)

PO1: Engineering Knowledge:

Apply the knowledge of mathematics, science, engineering fundamentals and an engineering specialization for the solution of complex engineering problems

PO2: Problem analysis:

Identify, formulate, research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO3: Design/development of solutions:

Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for public health and safety, and cultural, societal, and environmental considerations.

PO4: Conduct investigations of complex problems:

Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PO5: Modern tool usage:

Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling to complex engineering activities, with an understanding of the limitations.

PO6: The engineer and society:

Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal, and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

PO7: Environment and sustainability:

Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

PO8: Ethics:

Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO9: Individual and team work:

Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

P10: Communication:

Communicate effectively on complex engineering activities with the engineering community and with the society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

P11: Project management and finance:

Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

P12: Life-long learning:

Recognise the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

PEO1: Using a solid foundation in mathematical, scientific, engineering, and current computing principles, formulate, analyse, and resolve engineering issues.
PEO2: Apply artificial intelligence theory and concepts to analyse the requirements, realise technical specifications, and design engineering solutions.
PEO3: Through cross-disciplinary projects and a variety of professional activities, demonstrate technical proficiency, AI competency, and foster collaborative learning and a sense of teamwork.
PEO4: Provide graduates with solid knowledge, competence, and soft skills that will enable them to ethically contribute to societal demands and achieve sustainable advancement in emerging computer technologies through lifelong learning.

PSO1. Apply the principal concepts of AI Engineering to design, develop, deploy and prototype AI Subsystems
PSO2. Apply the knowledge gained pertaining to data storage, data analytics and AI concepts to solve real world business problems.
PSO3. Apply, analyse, design, develop, and test principles of AI concepts on Intelligent Systems

PEO 1: Work effectively in inter-disciplinary field with the knowledge of Artificial Intelligence and Machine Learning to develop appropriate solutions to real-world problems.
PEO 2: Excel in their professional careers and pursues advanced study in the area of machine learning and artificial intelligence.
PEO 3: Use ongoing education to apply their expertise to the technology transformation.
PEO 4: Excel as socially responsible engineers or entrepreneurs with high moral and ethical standards.

PSO 1: Ability to evaluate and apply knowledge of data engineering, artificial intelligence, machine learning, and human cognition to real-world issues in order to solve potential challenges.
PSO 2: Ability to acquire computational knowledge and project development abilities using novel tools and methodologies to tackle challenges in the fields related to Deep Learning, Machine learning, Artificial Intelligence.
PSO 3: Capacity to direct a team or firm that develops products and to use the knowledge learned to recognise actual research issues.